{"title":"A refutational approach to geometry theorem proving","authors":"Deepak Kapur","doi":"10.1016/0004-3702(88)90050-1","DOIUrl":null,"url":null,"abstract":"<div><div>A refutational method for proving universally quantified formulae in algebraic geometry is proposed. A geometry statement to be proved is usually stated as a finite set of hypotheses implying a conclusion. A hypothesis is either a polynomial equation expressing a geometric relation or a polynomial inequation (the negation of a polynomial equation) expressing a subsidiary condition that rules out degenerate cases and perhaps some general cases. A conclusion is a polynomial equation expressing a geometry relation to be derived. Instead of showing that the conclusion directly follows from the hypothesis equations and inequations, the proof-by-contradiction technique is employed. It is checked whether the negation of the conclusion is inconsistent with the hypotheses. This can be done by converting the hypotheses and the negation of the conclusion into a finite set of polynomial equations and checking that they do not have a common solution. There exist many methods for this check, thus giving a complete decision procedure for such geometry statements. This approach has been recently employed to automatically prove a number of interesting theorems in plane Euclidean geometry. A Gröbner basis algorithm is used to check whether a finite set of polynomial equations does not have a solution. Two other formulations of geometry problems are also discussed and complete methods for solving them using the Gröbner basis computations are given.</div></div>","PeriodicalId":8434,"journal":{"name":"Artificial Intelligence","volume":"37 1","pages":"Pages 61-93"},"PeriodicalIF":4.6000,"publicationDate":"1988-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0004370288900501","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
A refutational method for proving universally quantified formulae in algebraic geometry is proposed. A geometry statement to be proved is usually stated as a finite set of hypotheses implying a conclusion. A hypothesis is either a polynomial equation expressing a geometric relation or a polynomial inequation (the negation of a polynomial equation) expressing a subsidiary condition that rules out degenerate cases and perhaps some general cases. A conclusion is a polynomial equation expressing a geometry relation to be derived. Instead of showing that the conclusion directly follows from the hypothesis equations and inequations, the proof-by-contradiction technique is employed. It is checked whether the negation of the conclusion is inconsistent with the hypotheses. This can be done by converting the hypotheses and the negation of the conclusion into a finite set of polynomial equations and checking that they do not have a common solution. There exist many methods for this check, thus giving a complete decision procedure for such geometry statements. This approach has been recently employed to automatically prove a number of interesting theorems in plane Euclidean geometry. A Gröbner basis algorithm is used to check whether a finite set of polynomial equations does not have a solution. Two other formulations of geometry problems are also discussed and complete methods for solving them using the Gröbner basis computations are given.
期刊介绍:
The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.